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针对三相SPWM逆变器的故障,提出一种基于PSO-SVM的诊断模型。粒子群算法(PSO)是一种智能的启发式全局搜索优化方法,具有易理解、易实现、全局搜索能力强等特点,适合于支持向量机(SVM)的参数优化。采用小波变换的多分辨率方法来提取和分析故障信号,提取需要的故障向量,将故障特征向量作为PSO-SVM的输入,来进行训练和检测。通过仿真对比结果,验证所提出的这种方法是可行的,具有很好的故障诊断能力。
Aimed at the fault of three-phase SPWM inverter, a diagnosis model based on PSO-SVM is proposed. Particle swarm optimization (PSO) is an intelligent heuristic global search optimization method, which is easy to understand, easy to implement and has strong global search ability. It is suitable for parameter optimization of Support Vector Machine (SVM). The multi-resolution method based on wavelet transform is used to extract and analyze the fault signal, extract the required fault vector, and use the fault feature vector as the input of PSO-SVM for training and detection. By comparing the simulation results, it is feasible to validate the proposed method and have good fault diagnosis ability.